Reasoning with link keys

PhD position / Sujet de thèse

The purpose of the semantic web is to take advantage of formalised knowledge at the scale of the worldwide web. This has led to the release of a vast quantity of data, continuously growing, expressed in semantic web formalisms (RDF) generally called linked data [5]. Part of the added value of linked data lies in the links identifying the same entity in different datasets as it allows for making inferences across datasets. They may identify, for example, the same books and articles in different bibliographical data sources. So finding the manifestation of the same entity across several datasets is a crucial task of linked data [4].

One way of identifying entities is to use link keys, which generalise keys in relational databases to the case of two different RDF datasets [2]. An example of a link key is:

⟨auteur,creator⟩ ⟨titre,title⟩ linkkey ⟨Livre,Book⟩)

stating that whenever an instance of the class Livre has the same values for properties auteur and titre as an instance of class Book has for properties creator and title, then they denote the same entity.

Link keys can be used for data interlinking — they specify the properties and classes to compare for discovering links — but, interestingly, they can also be treated as logical axioms and can thus be combined with other kinds of knowledge, like ontologies, to support logical reasoning. Reasoning with link keys may be helpful to deduce further links, either directly or indirectly by deducing new link keys to use for interlinking.

The goal of this PhD is to study reasoning procedures for link keys. Two main directions are expected to be followed. First, and in line with the works on reasoning with ontologies written in OWL, mainly based on tableau methods for description logics (DLs) [6,3], the selected candidate will extend these methods for reasoning with link keys. Then, the student will study our previous work on rule-based methods for data interlinking [1] and adapt them to be able to reason with different kinds of link keys. The optimal joint use of these two approaches for data interlinking will be the ultimate objective of the PhD. The proposed methods will be implemented to come up with computationally efficient link key reasoners.

This PhD will be funded by the ELKER ANR project. The selected candidate is expected to be very involved in this project.

Expected results

Expected research skills


  1. Mustafa Al-Bakri, Manuel Atencia, Jérôme David, Steffen Lalande, and Marie-Christine Rousset. Uncertainty-sensitive reasoning for inferring sameas facts in linked data. In Proc. 22nd european conference on artificial intelligence (ECAI), Der Haague (NL), pages 698–706, 2016.
  2. Manuel Atencia, Jérôme David, and Jérôme Euzenat. Data interlinking through robust linkkey extraction. In Proc. 21st european conference on artificial intelligence (ECAI), Praha (CZ), pages 15–20, 2014.
  3. Franz Baader and Ulrike Sattler. An overview of tableau algorithms for description logics. Studia Logica, 69(1):5–40, 2001.
  4. Alfio Ferrara, Andriy Nikolov, and Franc ̧ois Scharffe. Data linking for the semantic web. International Journal of Semantic Web and Information Systems, 7(3):46–76, 2011.
  5. Tom Heath and Christian Bizer. Linked data: evolving the web into a global data space. Synthesis lectures on the semantic web: theory and technology. Morgan & Claypool, 2011.
  6. Carsten Lutz, Carlos Areces, Ian Horrocks, and Ulrike Sattler. Keys, nominals, and concrete domains. Journal of Artificial Intelligence Research, 23:667–726, 2005.

Requirements: The PhD candidate must have a master (or equivalent) in computer science.

Working environment: The candidate will join the mOeX team, a team of the Laboratoire d'Informatique de Grenoble (LIG), and a joint research team between the Université Grenoble Alpes (UGA) and Inria. The student will also collaborate closely with the Laboratoire d'Informatique Avancée de Saint-Denis (LIASD).

Work place: The position will be held at Inria Grenoble Rhône-Alpes (Montbonnot-Saint-Martin, France). Grenoble is the capital of the Alps in France with excellent train connections to Lyon (1h), Geneva (2h) and Paris (3h). Grenoble is a top skiing destination in Europe. The candidate is also expected to travel to Paris often during the PhD.

Doctoral school: Ecole doctorale Mathématiques, Sciences et technologies de l'information, Informatique — MSTII.

Advisors: Manuel Atencia (UGA & Inria) and Chan Le Duc (LIASD).

Hiring date: Four quarter 2017 (November 1, in principle).

Duration: 36 months.

Salary: the gross annual salary is 25,200 euros and the net annual salary 20,160 euros.

Contact: no
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File: Provide CV, motivation letter, master's dissertation and transcript of marks. Recommendation letters are a plus.